Оглавление
Abdulrahman Yarali. Intelligent Connectivity
Table of Contents
List of Tables
List of Illustrations
Guide
Pages
Intelligent Connectivity. AI, IoT, and 5G
Preface
Acknowledgement
Introduction. Intelligent Connectivity: Fusion of AI, IoT, and 5G
1 Technology Adoption and Emerging Trends. 1.1 Introduction
1.2 Trends in Business Technology
1.2.1 Trends that Could Disrupt the Industry
1.2.2 Adopting New Technologies
1.2.3 Best Practices and Risks Associated with Emerging Technologies
1.2.4 Power of Disruptive Technologies
1.2.5 Driving Strategy Around Our Priority
1.2.6 Strategic Partnerships to be Pursued
1.3 AI‐Fueled Organizations
1.4 Connectivity of Tomorrow
1.4.1 Intelligent Interfaces
1.5 Moving Beyond Marketing
1.6 Cloud Computing
1.7 Cybersecurity, Privacy, and Risk Management
1.8 Conclusion
References
2 Telecommunication Transformation and Intelligent Connectivity. 2.1 Introduction
2.1.1 Learning Algorithm and Its Connections to AI
2.1.2 Machine Learning as a Precursor to AI
2.1.3 Deep Learning and Realization of AI
2.1.4 Consideration of the Next Generation Wireless Technology
2.1.5 Potential of AI and 5G Network Technology Together
2.2 Cybersecurity Concerns in the 5G World
2.2.1 5G's Potential in Making Security a Priority
2.2.2 Key Features
2.2.2.1 Peak Data Rate
2.2.2.2 Mobile Data Volume
2.2.2.3 Mobility
2.2.2.4 Connected Devices
2.2.2.5 Energy Efficiency
2.2.2.6 Service Deployment
2.2.2.7 Reliability
2.2.2.8 Latency
2.3 Positive Effects of Addressing Cybersecurity Challenges in 5G
2.4 Intelligent Connectivity Use‐Cases
2.4.1 Transportation and Logistics
2.4.2 AI‐based Driver Assistance and Monitoring
2.4.3 Self‐Driving Vehicles
2.4.4 Deliveries with Unmanned Vehicles
2.5 Industrial and Manufacturing Operations
2.5.1 Factory Automation and Remote Control of Industrial Robots
2.5.2 Remote Inspections and Maintenance, and Worker's Training
2.6 Healthcare
2.6.1 Remote Health Monitoring and Illness Prevention
2.6.2 Remote Diagnosis and Medical Operation
2.7 Public Safety and Security
2.7.1 Intelligent Video‐Surveillance and Security Systems
2.7.2 Emergency Services and Border Controls
2.7.3 Other Sectors
2.7.3.1 Virtual Personal Assistance
2.7.3.2 3D Hologram Displays
2.8 Conclusion
References
3 The Internet of Things (IoT): Potentials and the Future Trends. 3.1 Introduction
3.2 Achieving the Future of IoT
3.3 Commercial Opportunities for IoT
3.4 The Industrial Internet of Things
3.4.1 How IIoT Works
3.4.2 Benefits of IIoT
3.4.3 IIoT versus IoT
3.4.4 IIoT Applications and Examples
3.4.5 Vendors in IIoT
3.4.6 The Future of IIoT
3.5 Future Impact of IoT in Our Industry
3.6 Data Sharing in the IoT Environment
3.7 IoT Devices for Environment Operation
3.7.1 Step One: Pick Your Protocol
3.7.2 Step Two: Understand Coexistence
3.7.3 Step Three: Pick Your Technique
3.7.4 Step Four: Create Your Test Plan
3.8 Interoperability Issues of IoT
3.9 IoT‐Cloud – Application
3.10 Regulation and Security Issues of IoT
3.11 Achieving IoT Innovations While Tackling Security and Regulation Issues
3.12 Future of IoT
3.13 Conclusion
References
4 The Wild Wonders of 5G Wireless Technology. 4.1 Introduction
4.1.1 First Generation (1G)
4.1.2 Second Generation (2G)
4.1.3 Third Generation (3G)
4.1.4 Advanced Third Generation (3.5G)
4.1.5 Fourth Generation (4G)
4.1.6 Fifth Generation (5G)
4.2 5G Architecture
4.2.1 Realizing New 5G Possibilities with the Intelligent Edge
4.3 5G Applications
4.3.1 5G and Video Surveillance
4.3.2 5G and Fixed Wireless Access (FWA)
4.4 5G Network Architecture
4.5 Security and Issues of 5G
4.6 IoT Devices in 5G Wireless
4.7 Big Data Analytics in 5G
4.8 AI Empowers a Wide Scope of Use Cases
4.9 Conclusion
References
5 Artificial Intelligence Technology. 5.1 Introduction
5.2 Core Concepts of Artificial Intelligence
5.3 Machine Learning and Applications
5.4 Deep Learning
5.5 Neural Networks Follow a Natural Model
5.6 Classifications of Artificial Intelligence
5.7 Trends in Artificial Intelligence
5.7.1 Artificial Intelligence in Energy
5.7.2 Artificial Intelligence in Healthcare
5.7.3 Artificial Intelligence in Education
5.7.4 Artificial Intelligence in Manufacturing
5.7.5 Artificial Intelligence in Financial Services
5.7.6 Artificial Intelligence in Transport
5.8 Challenges of Artificial Intelligence
5.8.1 Data
5.8.1.1 Data Quantity and Quality
5.8.1.2 Data Labeling
5.8.1.3 Clarity
5.8.1.4 Case‐Specific Learning
5.8.1.5 Bias
5.8.1.6 Model Accuracy
5.8.1.7 People
5.8.1.8 Deficiency of Field Experts
5.8.1.9 Business
5.8.1.10 Challenges in Evaluating Vendors
5.8.1.11 Challenges with Integration
5.8.1.12 Legal Matters
5.9 Funding Trends in Artificial Intelligence
5.9.1 Artificial Readiness
5.9.2 Foundational Readiness
5.9.3 Operational Readiness
5.9.4 Transformational Readiness
5.10 Conclusion
References
6 AI, 5G, and IoT: Driving Forces Towards the Industry Technology Trends. 6.1 Introduction
6.2 Fifth Generation of Network Technology
6.3 Internet of Things (IoT)
6.4 Industrial Internet of Things
6.5 IoT in the Automotive Industry
6.6 IoT in Agriculture
6.7 AI, IoT, and 5G Security
6.8 Conclusion
References
7 Intelligent Connectivity: New Capabilities to Bring Complex Use Cases. 7.1 Introduction
7.1.1 Artificial Intelligence
7.1.2 The Fifth Generation Networks
7.1.3 The Internet of Things
7.2 Machine‐to‐Machine Communication and the Internet of Things
7.3 Convergence of Internet of Things, Artificial Intelligence, and 5G
7.3.1 The Benefits of Intelligent Connectivity
7.4 Intelligent Connectivity Applications
7.4.1 Industry
7.4.2 Transport and Logistics
7.4.3 Healthcare
7.4.4 Security
7.4.5 Smart Homes and Personal Assistant
7.4.6 Wearable Technology
7.4.7 Entertainment
7.4.8 Communication
7.4.9 Resource Management
7.4.10 Agriculture
7.4.11 Education
7.5 Challenges and Risks of Intelligent Connectivity
7.5.1 Economic Risks
7.5.2 Risks to Human Safety and Agency
7.5.3 Social Risk
7.5.4 Secondary Risks
7.5.5 Confidentiality and Scalability
7.6 Recommendations
7.7 Conclusion
References
8 IoT : Laws, Policies, and Regulations. 8.1 Introduction
8.2 Recently Published Laws and Regulations
8.2.1 IoT Cybersecurity Improvement Act of 2017
8.3 Developing Innovation and Growing the Internet of Things (DIGIT) Act
8.4 General View
8.5 Relaxation of Laws by the Federal Aviation Administration (FAA)
8.6 Supporting Innovation of Self‐Driving Cars by Government Policies
8.6.1 Investment by US Department of Homeland Security
8.6.2 United States Guiding Principles for IoT Security
8.6.3 The United Kingdom on IoT
8.6.4 United States Department of Commerce
8.6.5 Federal Trade Commission and Creating an IoT Security Solution
8.7 Recommendations
8.8 Conclusion
References
9 Artificial Intelligence and Blockchain. 9.1 Introduction
9.2 Decentralized Intelligence
9.2.1 Data Protection
9.2.1.1 Information Monetization
9.2.2 Trusting AI Decision Making
9.2.3 AI and Encryption
9.3 Applications
9.3.1 The Coordination of Blockchain into AI
9.3.2 Essential Blockchain Benefits
9.4 How Artificial Intelligence and Blockchain Will Affect Society
9.4.1 Banking and Payments
9.4.2 Cybersecurity
9.4.3 Internet of Things
9.4.4 Unified Communications
9.4.5 Government
9.4.6 Crowdfunding and Donating to Charities
9.4.7 Healthcare
9.4.8 Rentals and Ride‐Sharing
9.5 Augmented Reality
9.5.1 Augmented Reality in the Production Context
9.5.2 How Augmented Reality Works
9.5.3 Marker and Marker‐Less AR
9.5.4 Layered AR
9.5.5 Projection AR
9.5.6 AR in Education
9.5.7 AR in Navigation
9.5.8 AR in Games
9.6 Mixed Reality
9.7 Virtual Reality
9.7.1 Virtual World
9.7.2 Mental Immersion
9.7.3 Physical Immersion
9.7.4 Tangible Feedback
9.7.5 Intelligence
9.7.6 Types of Virtual Reality
9.7.7 Semi‐Immersive
9.7.8 Completely Immersive
9.8 Key Components in a Virtual Reality System. 9.8.1 PC (Personal Computer)/Console/Smartphone
9.8.2 Head‐Mounted Display
9.8.3 Information Devices
9.8.4 Augmented Reality versus Virtual Reality
9.8.5 Benefits of Augmented Reality
9.9 Augmented Reality Uses
9.9.1 Retail
9.9.2 Real Estate
9.9.3 Interior Design
9.9.4 Tourism and Maps
9.9.5 Training and Education
9.9.6 Healthcare
9.10 Applications of Virtual Reality in Business
9.10.1 Training
9.10.2 Retail
9.10.3 Construction
9.10.4 Data Representation
9.10.5 Manufacture
9.11 The Future of Blockchain
9.12 Blockchain Applications
9.12.1 National Cryptographic Money
9.12.2 Blockchain into Government
9.12.3 Blockchain Specialists
9.13 Blockchain and the Internet of Things
9.14 Law Coordination
9.15 Collaboration for Blockchain Success
References
10 Digital Twin Technology. 10.1 Introduction
10.2 The Timeline and History of Digital Twin Technology
10.3 Technologies Employed in Digital Twin Models
10.3.1 Cloud Services
10.3.2 Cyber‐Physical Systems
10.4 The Dimension of Digital Twin Models
10.4.1 Digital Twin Data
10.4.2 Services in Digital Twins
10.4.3 Connection in Digital Twins
10.4.4 Physical Assets in Digital Twins
10.4.5 Virtual Entities in Digital Twins
10.5 Digital Twin and Other Technologies
10.5.1 Digital Twins and Internet of Things
10.5.2 Digital Twins and Artificial Intelligence
10.5.3 Digital Twins and Analytics
10.5.4 Digital Twins and Connectivity
10.5.5 Digital Twins and Machine Learning
10.6 Digital Twin Technology Implementation
10.7 Benefits of Digital Twins
10.8 Application of Digital Twins
10.8.1 Manufacturing
10.8.2 Healthcare
10.8.3 Smart Cities
10.8.4 Space Exploration
10.8.5 Business
10.9 Challenges of Digital Twins
10.9.1 Privacy and Data Security
10.9.2 Infrastructure
10.9.3 Data
10.9.4 Trust
10.9.5 Expectations
References
11 Artificial Intelligence, Big Data Analytics, and IoT. 11.1 Introduction
11.2 Analytics
11.2.1 Predictive Analytics
11.2.2 Prescriptive Analytics
11.2.3 Descriptive Analytics
11.3 AI Technology in Big Data and IoT
11.4 AI Technology Applications and Use Cases
11.5 AI Technology Impact on the Vertical Market
11.5.1 AI Predictive Analytics in the Vertical Market
11.6 AI in Big Data and IoT Market Analysis and Forecasts
11.7 Conclusion
References
12 Digital Transformation Trends in the Automotive Industry. 12.1 Introduction
12.2 Evolution of the Automotive Industry
12.3 Data‐Driven Business Model and Data Monetization
12.3.1 Big Data
12.3.2 Product Development
12.4 Services of the Data‐Driven Business Model
12.5 Values of New Services in the New Automotive Industry
12.5.1 Consumer Trust
12.6 Conclusion
References
13 Wireless Sensors/IoT and Artificial Intelligence for Smart Grid and Smart Home. 13.1 Introduction
13.2 Wireless Sensor Networks
13.3 Power Grid Impact
13.4 Benefits of the Smart Grid
13.5 Internet of Things
13.6 Internet of Things on the Smart Grid
13.6.1 Smart Grid Security
13.7 Smart Grid and Artificial Intelligence
13.8 Smart Grid Programming
13.9 Conclusion
References
14 Artificial Intelligence, 5G, and IoT: Security. 14.1 Introduction
14.2 Understanding IoT
14.3 Artificial Intelligence
14.4 5G Network
14.5 Emerging Partnership of Artificial Intelligence, IoT, 5G, and Cybersecurity
14.5.1 The Current State of IoT Security
14.6 Conclusion
References
15 Intelligent Connectivity and Agriculture. 15.1 Introduction
15.2 The Potential of Wireless Sensors and IoT in Agriculture
15.3 IoT Sensory Technology with Traditional Farming
15.3.1 IoT Sensors Available for Specific Agriculture Applications
15.3.2 Challenges Faced While Implementing Sensor Technologies
15.4 IoT Devices and Communication Techniques
15.5 IoT and all Crop Stages
15.6 Drone in Farming Applications
15.7 Conclusion
References
16 Applications of Artificial Intelligence, ML, and DL. 16.1 Introduction
16.2 Building Artificial Intelligence Capabilities
16.3 What is Machine Learning?
16.3.1 Machine Learning Methods
16.4 Deep Learning
16.4.1 Use Cases
16.4.2 The Working Mechanism
16.4.3 Deep Learning Models
16.4.4 Deep Learning and MATLAB®
16.5 Machine Learning vs. Deep Learning Comparison
16.5.1 Data Dependencies
16.5.2 Hardware Dependencies
16.5.3 Problem‐Solving Approach
16.6 Feature Engineering
16.6.1 Layerwise Features of Deep Learning
16.6.2 Execution Time in DL
16.6.3 Interpretability
16.7 Applications of Machine Learning
16.7.1 Virtual Personal Assistants
16.7.2 Predictions While Commuting
16.7.3 Video Surveillance
16.7.4 Social Media Services
16.7.5 Spam Email and Malware Filtering
16.7.6 Online Customer Support
16.7.7 Improved Search Engine Results
16.7.8 Product Recommendations
16.7.9 Fraud Detection on the Web
16.8 Applications of Deep Learning
16.8.1 Self‐Driving Cars
16.8.2 Healthcare
16.8.3 Voice Assistants and Search
16.8.4 Movies and Sound Effects
16.8.5 Auto Translator
16.8.6 Auto Text Generation
16.8.7 Automatic Handwriting Generation
16.8.8 Image Colorization
16.8.9 Earthquake Prediction
16.8.10 Detection of Brain Cancer
16.8.11 Finance
16.8.12 Energy Price
16.9 Future Trends
References
17 Big Data and Artificial Intelligence: Strategies for Leading Business Transformation. 17.1 Introduction
17.2 Big Data
17.2.1 Big Data Need for Organizations
17.2.2 Big Data and Applications
17.3 Machine Learning‐Based Medical Systems
17.4 Artificial Intelligence for Stock Market Predictions
17.4.1 Application of Artificial Intelligence by Investors
17.5 Trends in AI and Big Data Technologies Drive Business Innovation
17.5.1 Driving Innovation Through Big Data
17.5.2 The Convergence of AI and Big Data
17.5.3 How AI and Big Data Will Combine to Create Business Innovation
17.5.4 AI and Big Data for Technological Innovation
17.5.5 Disruptive Innovation
17.6 Advancements and New Entries
17.6.1 Recruitment of a Skilled Taskforce
17.6.2 Reliable Performance
17.7 AI and Production
17.7.1 Methodology
17.8 AI and ML Operations Research
17.8.1 Smart Maintenance
17.8.2 Intelligent Manufacturing
17.8.3 IoT‐Enabled Manufacturing
17.8.4 Cloud Manufacturing
17.8.5 Suitability of ML with AI
17.9 Collaboration Between Machines and Humans
17.10 Generative Designs
17.11 Adapting to a Changing Market
17.11.1 Conclusion
References
Index. a
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